Detect and track flaky RSpec specs
Almost every engineering team eventually experiences flaky specs. Martin Fowler sums up the problem nicely:
[Flaky specs] are a virulent infection that can completely ruin your entire test suite. As a result they need to be dealt with as soon as you can, before your entire deployment pipeline is compromised.
If you're experiencing flaky RSpec specs, BuildPulse can help. BuildPulse is a service that helps you detect and track flaky specs to save your engineering team time.
How can I detect flaky RSpec specs?
Identifying flaky RSpec specs requires two steps: generating JUnit XML reports for your test results and then analyzing those reports either on your own or automatically with BuildPulse. Below we’ll walk you through how to do this.
Generate JUnit XML reports for test results
JUnit XML serves as a standard format for integration between tools that deal with test results. BuildPulse reads test results using this format, and you can use it for your analysis as well.
In the steps below, we'll start with a Ruby project that has an existing RSpec test suite, and we'll add JUnit XML as an additional output format for the test suite. In each step, we'll show the Git diff for the change that we're making.
-
Add
rspec_junit_formatter
as a dependency.Verify that your
Gemfile
file includes the new dependency: -
Update your
.rspec
configuration file to output JUnit XML reports atspec/reports/rspec.xml
. -
Update your
.gitignore
file so that the JUnit report doesn't accidentally get checked into the repository. -
Commit these changes to your repository.
Analyze results to identify flaky specs
Now that your CI builds are generating JUnit XML reports, you can use those reports to find and track flaky specs as described below. Or, if you'd rather get this working in just a few minutes, you can automate everything with BuildPulse.
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Save the data to a central location
At the end of each CI build, save the following data to a central location (such as S3, etc.) for later processing:
- JUnit XML files
- Unique fingerprint for the code (such as the Git SHA)
- URL for the CI build
-
Analyze the data to find flaky specs
For builds that have the same unique code fingerprint (i.e., each of the builds that ran against the same exact code), parse the JUnit XML files to find any specs that passed in one build and failed in another build. When a test produces different results for the same code, we identify the test as flaky.
-
Keep track of the flaky specs you found
For each of the flaky specs identified in the previous step, store the key information about the flaky results. This information will show which specs are causing the most problems, and it will offer useful clues when investigating potential ways to fix the flakiness:
- Spec name
- Path to the file containing the spec
- Details for at least one passing result, including the timestamp and the build URL
- Details for each failure, including the timestamp, failure message, and the build URL
You can store this information anywhere that allows your team to track it over time and sort it to find the most frequent flaky specs (e.g., a database, a spreadsheet, an issue tracker). Or you can let BuildPulse handle all of the analysis and tracking for you.
Automatically detect and track flaky specs with BuildPulse
Most teams don't build their own issue trackers or databases. There are existing solutions and teams prefer to invest engineering time in their own core product instead. The same idea applies here. 😅
BuildPulse pays for itself in saved developer time. Instead of spending time building and maintaining a tool to detect, track, and rank flaky specs, BuildPulse does it for you.
To automate everything with BuildPulse:
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Start a free trial and follow the prompts to install BuildPulse on your repository.
-
Add a few lines to your CI script to send your JUnit XML reports to BuildPulse. See our guides for your CI provider:
- GitHub Actions
- CircleCI
- Semaphore
- Travis CI
- Buildkite (request early access)
- Jenkins (request early access)
Then, BuildPulse will automatically analyze your test results to identify flaky specs. The dashboard presents a rich visualization of your flaky specs over time, and it highlights the most disruptive ones so you know exactly where to focus first for maximum impact.

If you run into any trouble getting things set up, or if you have any questions at all, please get in touch.